Forward Deployed Engineer

About the role

Forward Deployed Engineers (FDEs) are integral members of Elixirr's delivery teams and internal functions. They are responsible for identifying high-leverage AI opportunities within real workflows, translating ambiguous business problems into concrete solutions, and building internal tools that accelerate Elixirr's operations.

Responsibilities

• Deploy into Elixirr delivery teams and internal functions to identify the highest-leverage AI opportunities inside real workflows.
• Sit with consultants, operators and end users to understand how decisions are actually made — then design around what you see, not what was described in a deck.
• Translate ambiguous business problems into concrete agentic solutions with clear success metrics and an honest view of the business case.
• Ideate, design, build and demo agents and agentic applications that execute real work — document processing, research, analysis, operational automations, internal copilots, workflow accelerators.
• Use modern agent frameworks and tooling (LangGraph, Semantic Kernel, AutoGen, CrewAI, MCP, A2A) pragmatically — pick the simplest thing that works.
• Instrument prototypes properly from day one: traces, evaluations, cost, latency and user feedback so decisions are grounded in data, not demos.
• Ship internal agents and tools that measurably accelerate how Elixirr delivers — from research and analysis to proposal shaping, document production and operational tasks.
• Extract reusable components, patterns and accelerators from each engagement back into Elixirr’s internal platform so the next team starts further up the curve.
• Partner with Elixirr’s production engineering team when a prototype earns the right to become enterprise-grade software.
• Packaging prototypes for handover: clear documentation, evals, architectural notes and known limitations — so the production team can industrialize quickly and safely.
• Stay engaged as a subject matter expert during productionization without becoming the bottleneck.
• Understand the economics of what you build — where value is created, where cost sits, and what a realistic adoption path looks like inside a real organization.
• Navigate security, compliance, change management and data realities without using them as reasons to slow down.
• Be the trusted technical voice leaders turn to when they want to know whether something is real or a demo — and say so honestly, either way.
• Where engagements are client-facing, engage credibly with senior client stakeholders, frame trade-offs clearly and keep the conversation grounded in outcomes.

Qualifications

• Experience: 5+ years as a software engineer shipping working systems; recent hands-on experience building LLM-powered or agentic applications. Track record of embedding with users or customers — consulting, startup founding engineer, FDE, solutions engineering, internal platform teams, or similar.
• Technical Expertise: Strong full-stack or backend engineering fundamentals — Python, TypeScript/Node.js or similar — and the willingness to touch whatever layer the problem needs. Practical fluency with modern LLMs, agent frameworks, RAG, tool use, evaluation and observability tooling. Cloud-native experience on AWS and/or Azure (GCP a plus), with a working understanding of identity, data and deployment patterns. Daily use of AI-assisted developer tools and agentic coding workflows — you build with AI, not just about it.
• Business Acumen: Able to read a business: you understand revenue, cost, workflow and decision-making, and you use that understanding to shape what gets built and why. Comfortable framing a problem as a business case, defending trade-offs and knowing when to stop building. Commercially aware — you understand that a useful prototype that people actually adopt beats an elegant one that nobody uses.
• Mindset: Bias to action: you’d rather ship a rough v1 and learn than design the perfect v3 in a deck. Product sense: you care about the user, the workflow and the outcome — not just the code. Comfortable with ambiguity — briefs change, data is incomplete, priorities move; you keep shipping. Teacher instinct: you make the people around you better without being asked to.

Nice to have

• Founding or early engineer experience at a startup.
• Experience in regulated industries (financial services, insurance, healthcare, energy, public sector).
• Open-source contributions or public writing/speaking on agentic systems.